Automatic Extraction Method of Green Tide Based on Mixed Pixel Decomposition Feedback Adjustment

Since 2007, recurring green tides in the Yellow Sea have caused substantial ecological and socioeconomic impacts. Accurate and efficient automated extraction from remote sensing images is vital for monitoring these events. However, current extraction methods rely on a one-way strategy, where mixed pixels are first extracted and then decomposed. This often leads to under or overextraction due to the complex distribution of green tides and varying background water environments, and these errors are difficult to fully eliminate even after decomposition. This article proposes a novel approach that integrates mixed pixel decomposition with a feedback adjustment module to refine the extraction threshold. Utilizing the Google Earth Engine platform, we employ a convolutional neural network to establish relationships between algal endmembers and water endmembers in remote sensing images. Based on this, we perform mixed pixel decomposition on moderate resolution imaging spectroradiometer images. The feedback adjustment mechanism then refines the threshold in the adaptive OTSU method for extracting green tides, enabling more accurate and efficient automatic extraction in varying environments. Comparative analysis with high-resolution sensors [e.g., panchromatic (PAN), wide-field of view (WFV), and charge-coupled device (CCD)] shows an average relative difference of 8.19% in the extracted coverage area. This approach offers critical support for large-scale, long-term monitoring and early warning of green tides, and serves as a methodological reference for future research on marine algal bloom disasters.

• Publication year

  2025

• Venue

  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/JSTARS.2024.3504561
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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  2019influential reference
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  2016influential reference
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• Recurrence of the world's largest green-tide in 2009 in Yellow Sea, China: Porphyra yezoensis aquaculture rafts confirmed as nursery for macroalgal blooms.

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• The possibility analysis of habitats, origin and reappearance of bloom green alga (Enteromorpha prolifera) on inshore of western Yellow Sea

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• Ecological and physiological controls of species composition in green macroalgal blooms.

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